





"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


SCREAMING_SNAKE_CASE__   =  logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__   =  {
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}

class 						lowercase   (   _UpperCAmelCase   ):
      _SCREAMING_SNAKE_CASE							      = 'roberta-prelayernorm'





      def __init__(			self ,		lowercase=50_265 ,		lowercase=768 ,		lowercase=12 ,		lowercase=12 ,		lowercase=3_072 ,		lowercase="gelu" ,		lowercase=0.1 ,		lowercase=0.1 ,		lowercase=512 ,		lowercase=2 ,		lowercase=0.02 ,		lowercase=1e-12 ,		lowercase=1 ,		lowercase=0 ,		lowercase=2 ,		lowercase="absolute" ,		lowercase=True ,		lowercase=None ,		**lowercase ,		)						->	List[str]:
            super().__init__(pad_token_id=lowercase ,		bos_token_id=lowercase ,		eos_token_id=lowercase ,		**lowercase					)

            lowerCAmelCase    		=			vocab_size
            lowerCAmelCase    		=			hidden_size
            lowerCAmelCase    		=			num_hidden_layers
            lowerCAmelCase    		=			num_attention_heads
            lowerCAmelCase    		=			hidden_act
            lowerCAmelCase    		=			intermediate_size
            lowerCAmelCase    		=			hidden_dropout_prob
            lowerCAmelCase    		=			attention_probs_dropout_prob
            lowerCAmelCase    		=			max_position_embeddings
            lowerCAmelCase    		=			type_vocab_size
            lowerCAmelCase    		=			initializer_range
            lowerCAmelCase    		=			layer_norm_eps
            lowerCAmelCase    		=			position_embedding_type
            lowerCAmelCase    		=			use_cache
            lowerCAmelCase    		=			classifier_dropout







class 						lowercase   (   _UpperCAmelCase   ):





      @property
      def        _snake_case     (			self					)						->	Mapping[str, Mapping[int, str]]:
            if self.task == "multiple-choice":
                  lowerCAmelCase    		=			{0: """batch""", 1: """choice""", 2: """sequence"""}
            else:
                  lowerCAmelCase    		=			{0: """batch""", 1: """sequence"""}
            return OrderedDict(
                [
                    ("""input_ids""", dynamic_axis),
                    ("""attention_mask""", dynamic_axis),
                ]					)













"""simple docstring"""





def      UpperCAmelCase__				(    SCREAMING_SNAKE_CASE	:		int				,		SCREAMING_SNAKE_CASE	:		int     ):







      '''simple docstring'''




      if a < 0 or b < 0:
            raise ValueError("""the value of both inputs must be positive"""     )
      lowerCAmelCase    		=			str(bin(SCREAMING_SNAKE_CASE     )     )[2:]  # remove the leading "0b"
      lowerCAmelCase    		=			str(bin(SCREAMING_SNAKE_CASE     )     )[2:]
      lowerCAmelCase    		=			max(len(SCREAMING_SNAKE_CASE     )				,		len(SCREAMING_SNAKE_CASE     )     )
      return "0b" + "".join(
          str(int("""1""" in (char_a, char_b)     )     )
          for char_a, char_b in zip(a_binary.zfill(SCREAMING_SNAKE_CASE     )				,		b_binary.zfill(SCREAMING_SNAKE_CASE     )     )     )


if __name__ == "__main__":
       import doctest

       doctest.testmod()






